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#2
by
osanseviero
- opened
src/distilabel_dataset_generator/apps/sft.py
CHANGED
@@ -1,5 +1,6 @@
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import multiprocessing
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import time
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import gradio as gr
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import pandas as pd
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@@ -17,7 +18,6 @@ from src.distilabel_dataset_generator.pipelines.sft import (
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from src.distilabel_dataset_generator.utils import (
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get_login_button,
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get_org_dropdown,
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get_token,
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)
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@@ -65,8 +65,8 @@ def generate_dataset(
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private=True,
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org_name=None,
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repo_name=None,
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token=None,
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progress=gr.Progress(),
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):
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repo_id = (
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f"{org_name}/{repo_name}"
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@@ -78,12 +78,6 @@ def generate_dataset(
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raise gr.Error(
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"Please provide a repo_name and org_name to push the dataset to."
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)
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try:
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whoami(token=token)
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except Exception:
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raise gr.Error(
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"Provide a Hugging Face token with write access to the organization you want to push the dataset to."
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)
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if num_turns > 4:
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num_turns = 4
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@@ -132,7 +126,7 @@ def generate_dataset(
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repo_id=repo_id,
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private=private,
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include_script=False,
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token=token,
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)
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# If not pushing to hub generate the dataset directly
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@@ -152,11 +146,16 @@ def generate_pipeline_code() -> str:
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return pipeline_code
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with gr.Blocks(
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title="⚗️ Distilabel Dataset Generator",
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head="⚗️ Distilabel Dataset Generator",
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) as app:
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gr.Markdown("## Iterate on a sample dataset")
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with gr.Column() as main_ui:
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dataset_description = gr.TextArea(
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@@ -209,7 +208,7 @@ with gr.Blocks(
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# Add a header for the full dataset generation section
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gr.Markdown("## Generate full dataset")
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gr.Markdown(
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"Once you're satisfied with the sample, generate a larger dataset and push it to the
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)
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with gr.Column() as push_to_hub_ui:
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@@ -231,8 +230,6 @@ with gr.Blocks(
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)
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with gr.Row(variant="panel"):
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get_login_button()
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hf_token = gr.Textbox(label="HF token", type="password")
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org_name = get_org_dropdown()
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repo_name = gr.Textbox(label="Repo name", placeholder="dataset_name")
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private = gr.Checkbox(
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@@ -277,7 +274,6 @@ with gr.Blocks(
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private,
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org_name,
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repo_name,
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hf_token,
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],
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outputs=[table],
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show_progress=True,
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@@ -296,5 +292,4 @@ with gr.Blocks(
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label="Distilabel Pipeline Code",
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)
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app.load(get_token, outputs=[hf_token])
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app.load(get_org_dropdown, outputs=[org_name])
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import multiprocessing
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import time
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+
from typing import Union
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import gradio as gr
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import pandas as pd
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from src.distilabel_dataset_generator.utils import (
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get_login_button,
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get_org_dropdown,
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)
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private=True,
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org_name=None,
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repo_name=None,
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progress=gr.Progress(),
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oauth_token: Union[gr.OAuthToken, None]
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):
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repo_id = (
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f"{org_name}/{repo_name}"
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raise gr.Error(
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"Please provide a repo_name and org_name to push the dataset to."
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)
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if num_turns > 4:
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num_turns = 4
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repo_id=repo_id,
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private=private,
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include_script=False,
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token=oauth_token.token,
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)
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# If not pushing to hub generate the dataset directly
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return pipeline_code
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css = """
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.main_ui_logged_out{opacity: 0.3; pointer-events: none}
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"""
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with gr.Blocks(
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title="⚗️ Distilabel Dataset Generator",
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head="⚗️ Distilabel Dataset Generator",
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css=css
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) as app:
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get_login_button()
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gr.Markdown("## Iterate on a sample dataset")
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with gr.Column() as main_ui:
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dataset_description = gr.TextArea(
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# Add a header for the full dataset generation section
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gr.Markdown("## Generate full dataset")
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gr.Markdown(
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"Once you're satisfied with the sample, generate a larger dataset and push it to the Hub."
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)
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with gr.Column() as push_to_hub_ui:
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)
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with gr.Row(variant="panel"):
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org_name = get_org_dropdown()
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repo_name = gr.Textbox(label="Repo name", placeholder="dataset_name")
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private = gr.Checkbox(
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private,
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org_name,
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repo_name,
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],
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outputs=[table],
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show_progress=True,
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label="Distilabel Pipeline Code",
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)
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app.load(get_org_dropdown, outputs=[org_name])
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src/distilabel_dataset_generator/utils.py
CHANGED
@@ -47,18 +47,17 @@ def get_duplicate_button():
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return gr.DuplicateButton(size="lg")
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def list_orgs(
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if
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data = whoami(token)
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organisations = [
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entry["entity"]["name"]
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for entry in data["auth"]["accessToken"]["fineGrained"]["scoped"]
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if "repo.write" in entry["permissions"]
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]
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organisations.append(data["name"])
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return list(set(organisations))
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else:
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return []
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def get_org_dropdown(token: OAuthToken = None):
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return gr.DuplicateButton(size="lg")
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def list_orgs(oauth_token: OAuthToken = None):
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if oauth_token is None:
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return []
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data = whoami(oauth_token.token)
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organisations = [
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entry["entity"]["name"]
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for entry in data["auth"]["accessToken"]["fineGrained"]["scoped"]
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if "repo.write" in entry["permissions"]
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]
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organisations.append(data["name"])
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return list(set(organisations))
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def get_org_dropdown(token: OAuthToken = None):
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